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Cited by 16Physical Activity and HealthContext-Aware Activity Recognition SystemsCardiovascular Health and Risk Factors

Cardiovascular mortality risk prediction using objectively measured physical activity phenotypes in NHANES 2003–2006

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Ledbetter, Mark K., Tabacu, Lucia, Leroux, Andrew, Crainiceanu, Ciprian M., Smirnova, Ekaterina·2022·Preventive Medicine
DOI 10.1016/j.ypmed.2022.107303PMC PMC10159260
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Abstract

Increased physical activity (PA) has been associated with a decreased risk of cardiovascular disease (CVD) and mortality. However, most previous studies use self-reported PA instead of objectively measured PA assessed by wearable accelerometers. To the best of our knowledge, there have not been studies that quantified the univariate and multivariate ability of objectively measured PA summaries to predict the risk of CVD mortality. We investigate the ability of objectively measured PA summary variables to predict CVD mortality: as individual predictors, as part of the best multivariate model incorporating traditional predictors, and as additions to the best multivariate model using only traditional CVD predictors. Data were collected in the National Health and Nutrition Examination Survey 2003-2006 waves for US participants aged 50-85. The predictive ability was measured using Concordance, sometimes referred to as the C-statistic. Specifically, we calculated 10-fold cross-validated concordance (CVC) in survey-weighted Cox proportional hazard models. The best univariate predictor of CVD mortality was total activity count (outperformed age). In multivariate models, two of the eight predictors identified using the improvement in CVC threshold of 0.001 were PA measures (CVC = 0.844). The best model without physical activity (7 predictors) had CVC of 0.830. The addition of PA measures to the best traditional model was significantly better at predicting CVD mortality (P < 0.001). Accelerometer-derived PA measures have excellent cardiovascular mortality prediction performance. Wearable accelerometers have a potential for assessment of individuals' CVD mortality risks.

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  • Existing studies have demonstrated that objectively measured physical activity could be a potential predictor for cardiovascular disease mortality and cancer mortality in the general population.

    “In addition, existing studies have demonstrated that objectively measured PA could be a potential predicator for cardiovascular disease (CVD) mortality and cancer mortality in the general population15,16.”

    From Accelerometer-derived physical activity and mortality in individuals with type 2 diabetes (2024) · cites this paper as [16]

    The Discussion reports that accelerometer-derived physical activity measures predicted CVD mortality in a US non-institutionalized sample, and the Abstract specifies participants aged 50–85. The paper does not report a finding about cancer mortality, and its study population is narrower than the general population claimed. (LLM, conf=0.89)

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Research works printed but not linked: 1

  1. Di J, Leroux A, Urbanek J, Varadhan R, Spira AP, Schrack J,, 2017. Patterns of sedentary and active time accumulation are associated with mortality in US adults: The NHANES study. bioRxiv, p. 182337.

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Authors
Ledbetter, M. K., Tabacu, L., Leroux, A., Crainiceanu, C. M., & Smirnova, E.
Affiliations
  • University of Lynchburg (US)
  • Old Dominion University (US)
  • University of Colorado Anschutz (US)
  • Johns Hopkins University (US)
  • Virginia Commonwealth University (US)
Corresponding author
Smirnova, Ekaterina
ORCID
Venue
Preventive Medicine
Publisher
Elsevier BV
Published
2022-11
Volume
164
Pages
107303
ISSN
0091-7435 (ISSN-L)
DOI
10.1016/j.ypmed.2022.107303
PMC
PMC10159260
OpenAlex
W4305072390
Cited by
16
References
45
Citations by year
2026: 7 · 2025: 3 · 2024: 3 · 2023: 3
FWCI
1.39
Type
journal article
Language
en
Open access
Licence
Locations
  • Preventive Medicine (acceptedVersion)
  • PubMed (publishedVersion)
  • PubMed Central (acceptedVersion)
Funders
  • National Institute of Neurological Disorders and Stroke
  • Virginia Commonwealth University (NS060910)
  • National Institutes of Health (CTSA 5KL2TR002648, CTSA UL1TR002649)
Topics
  • Health Sciences › Medicine › Physiology › Physical Activity and Health
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Context-Aware Activity Recognition Systems
  • Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Cardiovascular Health and Risk Factors
Keywords
cardiovascular mortality, physical activity, accelerometer, wearable activity trackers, mortality prediction, NHANES, older adults, concordance index, Cox proportional hazards model
MeSH terms
Cardiovascular Diseases, Humans, Nutrition Surveys, Phenotype, Risk Factors, Exercise

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